Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer

Combination of intravoxel incoherent motion histogram parameters and clinical characteristics for predicting response to neoadjuvant chemoradiation in patients with locally advanced rectal cancer

OBJECTIVE

To explore the value of histogram parameters derived from intravoxel incoherent motion (IVIM) for predicting response to neoadjuvant chemoradiation (nCRT) in patients with locally advanced rectal cancer (LARC).

METHODS

A total of 112 patients diagnosed with LARC who underwent IVIM-DWI prior to nCRT were enrolled in this study. The true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and microvascular volume fraction (f) calculated from IVIM were recorded along with the histogram parameters. The patients were classified into the pathological complete response (pCR) group and the non-pCR group according to the tumor regression grade (TRG) system. Additionally, the patients were divided into low T stage (yp T0-2) and high T stage (ypT3-4) according to the pathologic T stage (ypT stage). Univariate logistic regression analysis was implemented to identify independent risk factors, including both clinical characteristics and IVIM histogram parameters. Subsequently, models for Clinical, Histogram, and Combined Clinical and Histogram were constructed using multivariable binary logistic regression analysis for the purpose of predicting pCR. The area under the receiver operating characteristic (ROC) curve (AUCs) was employed to evaluate the diagnostic performance of the three models.

RESULTS

The values of D_ kurtosis, f_mean, and f_ median were significantly higher in the pCR group compared with the non-pCR group (all P < 0.05). The value of D*_ entropy was significantly lower in the pCR group compared with the non-pCR group (P < 0.05). The values of D_ kurtosis, f_mean, and f_ median were significantly higher in the low T stage group compared with the high T stage group (all P < 0.05). The value of D*_ entropy was significantly lower in the low T stage group compared with the high T stage group (P < 0.05). The ROC curves indicated that the Combined Clinical and Histogram model exhibited the best diagnostic performance in predicting the pCR patients with AUCs, sensitivity, specificity, and accuracy of 0.916, 83.33%, 85.23%, and 84.82%.

CONCLUSIONS

The histogram parameters derived from IVIM have the potential to identify patients who have achieved pCR. Moreover, the combination of IVIM histogram parameters and clinical characteristics enhanced the diagnostic performance of IVIM histogram parameters.

Wall characteristics of atherosclerotic middle cerebral arteries in patients with single or multiple infarcts: A high-resolution MRI Study

Background and purpose

Understanding the stroke mechanism of middle cerebral artery (MCA) atherosclerosis may inform secondary prevention. The aim of this study was to explore the relationship between vascular wall characteristics and infarction patterns using high-resolution magnetic resonance imaging (HRMRI) and diffusion-weighted imaging (DWI).

Methods

From November 2018 to March 2021, patients with acute ischemic stroke due to MCA atherosclerotic disease were retrospectively analyzed. The wall characteristics of atherosclerotic MCA, including conventional characteristics and histogram-defined characteristics, were evaluated using HRMRI. Patients were divided into single-infarction and multiple-infarction groups based on DWI, and wall characteristics were compared between the two groups.

Results

Of 92 patients with MCA plaques, 59 patients (64.1%) had multiple infarcts, and 33 (35.9%) had single infarcts. The histogram-defined characteristics showed no differences between the single-infarction and multiple-infarction groups (P&gt;0.05). Plaque burden, degree of stenosis, and prevalence of intraplaque hemorrhage (IPH) were significantly greater in the multiple-infarction group than in the single-infarction group (plaque burden: P = 0.001; degree of stenosis: P = 0.010; IPH: P = 0.019). Multivariate analysis showed that plaque burden (odds ratio: 1.136; 95% confidence interval: 1.054–1.224, P = 0.001) and IPH (odds ratio: 5.248; 95% confidence interval: 1.573–17.512, P = 0.007) were independent predictors for multiple infarction.

Conclusion

IPH and plaque burden are independently associated with multiple infarcts. HRMRI may provide new insight into the mechanisms underlying the different MCA infarction patterns.